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Throughput analysis of a DS/SSMA unslotted ALOHA system with two user classes

机译:具有两个用户类别的DS / SSMA非开槽ALOHA系统的吞吐量分析

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We propose a direct-sequence spread spectrum multiple access (DS/SSMA) unslotted ALOHA system with two user classes and analyze the throughput of the proposed system. Mobile stations (MSs) are divided into two classes according to payment or traffic characteristics, such as delay-intolerant and delay-tolerant. Different permission probabilities are assigned to each class so that the appropriate quality of service can be provided. We assume that the generation of class 1 and 2 messages are Poisson distributed and the message is divided into several packets before transmission. The system is modeled as a two-dimensional Markov chain under the assumption that the number of packets transmitted immediately by both user classes is geometrically distributed and the packet length is constant. We calculate the packet success probability and the throughput as a function of the signal-to-noise ratio (SNR) during packet transmission, considering the number of overlapped class 1 and 2 messages and the amount of their time overlap. Moreover, we show that the proposed system differentiates user packets according to class and maintains a high throughput even under heavy traffic conditions using access control based on the channel load.
机译:我们提出了具有两个用户类别的直接序列扩频多址(DS / SSMA)无时隙ALOHA系统,并分析了所提出系统的吞吐量。根据付费或话务特性,将移动站(MS)分为两类,例如延迟不容忍和延迟容忍。将不同的权限概率分配给每个类别,以便可以提供适当的服务质量。我们假设1类和2类消息的生成是泊松分布的,并且在传输之前将消息划分为几个数据包。该系统被建模为二维马尔可夫链,其前提是两个用户类别立即发送的数据包的数量是几何分布的,并且数据包的长度是恒定的。考虑到重叠的1类和2类消息的数量以及它们的时间重叠量,我们根据数据包传输过程中信噪比(SNR)的函数来计算数据包成功概率和吞吐量。此外,我们表明,所提出的系统可以根据类别区分用户数据包,即使使用基于信道负载的访问控制,即使在交通繁忙的情况下也可以保持较高的吞吐量。

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